--- res: bibo_abstract: - In order to respond reliably to specific features of their environment, sensory neurons need to integrate multiple incoming noisy signals. Crucially, they also need to compete for the interpretation of those signals with other neurons representing similar features. The form that this competition should take depends critically on the noise corrupting these signals. In this study we show that for the type of noise commonly observed in sensory systems, whose variance scales with the mean signal, sensory neurons should selectively divide their input signals by their predictions, suppressing ambiguous cues while amplifying others. Any change in the stimulus context alters which inputs are suppressed, leading to a deep dynamic reshaping of neural receptive fields going far beyond simple surround suppression. Paradoxically, these highly variable receptive fields go alongside and are in fact required for an invariant representation of external sensory features. In addition to offering a normative account of context-dependent changes in sensory responses, perceptual inference in the presence of signal-dependent noise accounts for ubiquitous features of sensory neurons such as divisive normalization, gain control and contrast dependent temporal dynamics.@eng bibo_authorlist: - foaf_Person: foaf_givenName: Matthew J foaf_name: Chalk, Matthew J foaf_surname: Chalk foaf_workInfoHomepage: http://www.librecat.org/personId=2BAAC544-F248-11E8-B48F-1D18A9856A87 orcid: 0000-0001-7782-4436 - foaf_Person: foaf_givenName: Paul foaf_name: Masset, Paul foaf_surname: Masset - foaf_Person: foaf_givenName: Boris foaf_name: Gutkin, Boris foaf_surname: Gutkin - foaf_Person: foaf_givenName: Sophie foaf_name: Denève, Sophie foaf_surname: Denève bibo_doi: 10.1371/journal.pcbi.1005582 bibo_issue: '6' bibo_volume: 13 dct_date: 2017^xs_gYear dct_isPartOf: - http://id.crossref.org/issn/1553734X dct_language: eng dct_publisher: Public Library of Science@ dct_title: Sensory noise predicts divisive reshaping of receptive fields@ ...